Microsoft Analyzing Data with Microsoft Power BI (DA-100 Deutsch Version) : DA-100 Deutsch

  • Exam Code: DA-100 Deutsch
  • Exam Name: Analyzing Data with Microsoft Power BI (DA-100 Deutsch Version)
  • Updated: Aug 06, 2026
  • Q & A: 150 Questions and Answers

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Understanding functional and technical aspects of Exam DA-100: Analyzing Data with Microsoft Power BI Analyze the data

The following will be discussed in MICROSOFT DA-100 exam dumps:

  • Use the decomposition tree visual to break down a measure
  • Enhance reports to expose insights
  • Use the Q&A visual
  • Perform top N analysis
  • Use the Play Axis feature of a visualization
  • Explore statistical summary
  • Apply slicers and filters
  • Perform advanced analysis
  • Apply conditional formatting
  • Conduct Time Series analysis
  • Use the Key Influencers to explore dimensional variances
  • Personalize visuals
  • Use groupings and binnings
  • Identify outliers
  • Add a Quick Insights result to a report
  • Apply AI Insights
  • Create reference lines by using Analytics pane

Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/da-100

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Career Opportunities and Pay

After getting through with DA-100 exam and earning the Microsoft Certified: Data Analyst Associate certification, you will be able to offer more for big business companies that need more analytical power that Excel cannot provide. This opens up multiple job opportunities with decent average annual salaries. Below are some of them as covered by Payscale:

  • Web Data Analyst: $67k.
  • Data Analyst: $61k;
  • IT Operation Analyst: $56k;

Microsoft DA-100 Deutsch Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Visualize the data25%- Enforce accessibility
  • 1. Use accessibility features
  • 2. Configure tab order
  • 3. Design accessible reports
- Create reports
  • 1. Format and configure visualizations
  • 2. Create and manage bookmarks
  • 3. Add visualization items to reports
  • 4. Import a custom visual
  • 5. Choose an appropriate visualization type
  • 6. Apply slicing and filtering
  • 7. Configure conditional formatting
- Create dashboards
  • 1. Manage tiles on a dashboard
  • 2. Configure data alerts
  • 3. Use the Q&A feature
  • 4. Set mobile view
Topic 2: Analyze the data15%- Perform advanced analysis
  • 1. Use advanced analytical custom visuals
  • 2. Perform What-if analysis
  • 3. Use the Analyze feature
  • 4. Identify outliers
- Enhance reports for usability and storytelling
  • 1. Create custom tooltips
  • 2. Apply sorting
  • 3. Configure navigation for a report
  • 4. Edit and configure interactions between visuals
  • 5. Group and layer visuals
  • 6. Configure bookmarks
  • 7. Configure sync slicers
Topic 3: Deploy and maintain deliverables10%- Create and manage workspaces
  • 1. Assign workspace roles
  • 2. Configure and update a workspace app
  • 3. Create and configure a workspace
- Manage datasets
  • 1. Configure cross-workspace sharing
  • 2. Configure a dataset scheduled refresh
  • 3. Configure row-level security group membership
  • 4. Provide access to datasets
Topic 4: Model the data30%- Create measures by using DAX
  • 1. Create calculated measures
  • 2. Use DAX aggregation functions
  • 3. Create semi-additive measures
  • 4. Implement Time Intelligence using DAX
  • 5. Use DAX logical functions
- Design a data model
  • 1. Define quick measures
  • 2. Design and implement role-playing dimensions
  • 3. Define a relationship's cross-filter direction and security filtering
  • 4. Configure table and column properties
  • 5. Define the tables
- Develop a data model
  • 1. Create calculated columns
  • 2. Create hierarchies
  • 3. Implement row-level security roles
  • 4. Create calculated tables
- Optimize model performance
  • 1. Improve performance by choosing optimal data types
  • 2. Optimize Power Query transformations
  • 3. Improve performance by identifying and removing unnecessary rows and columns
Topic 5: Prepare the data20%- Get data from different data sources
  • 1. Identify and connect to a data source
  • 2. Change data source settings
  • 3. Select a storage mode
  • 4. Select a shared dataset or create a local dataset
  • 5. Choose an appropriate Power BI data source
- Clean the data
  • 1. Evaluate data, including data statistics and column properties
  • 2. Resolve inconsistencies, unexpected or null values, and data quality issues
  • 3. Resolve data import errors
- Transform and load the data
  • 1. Select appropriate column data types
  • 2. Create and transform columns
  • 3. Define relationship cardinality and cross-filter direction
  • 4. Create and transform tables
  • 5. Design a star schema
- Profile the data
  • 1. Examine data structures
  • 2. Interpret data distribution and variance
  • 3. Identify data anomalies

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